Data Visualization with R

require(ggplot2)
require(ggthemes)
require(xtable)
require(qdata)
data(bands)

The overall appearance of plots is controlled by the theming system, an important component of ggplot2 grammar. We started the exploration of theming system in the previous chapters, in particular in Legend Customization, Axes Customization and Facet Customization, where we saw how themes give us the control of non-data elements of the plot like fonts, ticks, panel strip, legend keys, ..

In this chapter we will deeepen the theming system structure and we will answer to the most frequently asked questions about plot customization.

Theming system structure

ggplot2 has a default theme, called theme_grey(), with a light grey background and white gridlines.
A theme, or theme function defines the settings of a collection of theme elements for the purpose of creating a specific style of graphics production.

Let us see an example, considering the relationship between humidity and viscosity by pressure type in bands dataset:

pl <- ggplot(data = bands, mapping = aes(x= humidity, y = viscosity, colour =press_type)) +
  geom_point()
pl

In particular, a theme function is composed of:

  • theme elements, which refer to individual attributes of a graphic that are independent of the data and that you can control, such as font size, axis ticks, appearance of grid lines or background color of a legend;

  • theme element functions, which enables you to modify the settings of certain theme elements. In particular, each theme element is associated with an element function, which describes the visual properties of that element.

Each theme element has a default value that can be locally modified in a specific ggplot object by using theme() function.

Suppose we want to modify the colour of axis lines:

pl + 
  theme(axis.line.x = element_line(colour = "black"),
        axis.line.y = element_line(colour = "black"))

In particular, axis.line.x and axis.line.y are the theme elements that control the appearance of x and y axis respectively and element_line() is the theme element function that allows us to modify the theme elements.

Moreover, if you don’ like theme_grey() you can decide to totally replace it by setting another theme function (complete theme). Let us set theme_bw(), a theme with white background and thin grey grid lines:

pl + 
  theme_bw()

Understanding how dealing with theme element functions and theme elements is very important in plot customization phase.

The most important theme element functions are:

  • element_text(): controls the drawing of labels and headings.
  • element_line(): draws lines and segments such as graphics region boundaries, axis tick marks and grid lines.
  • element_rect(): draws rectangles. It is mostly used for background elements and legend keys.
  • element_blank(): draws nothing. This function has no arguments.

There are around 40 unique theme elements that controls the appearance of the plots. They can be roughly grouped into five categories: plot, axis, legend, panel and facet.

Let us schematize them:

  • plot theme elements
Theme Element Description Element Function Associated
plot.background plot background element_rect()
plot.title plot title element_text()
plot.margin margins around plot unit()

unit() is a theme function exported by ggplot2 from grid package. It controls grid.

Let us see an example:

pl + 
  labs(title = "Plot title") +
  theme(plot.title = element_text(size = 36, hjust = 0, colour = "lightslateblue", face = "italic"),
        plot.background = element_rect(fill = "lightsteelblue1", colour = "black", size = 2, linetype = "solid"),
        plot.margin = unit(c(2, 2, 2, 2), "cm"))

  • axis theme elements
Theme Element Description Element Function Associated
axis.line line parallel to axis (hidden in default theme) element_line()
axis.text tick labels element_text()
axis.text.x x-axis tick labels element_text()
axis.text.y y-axis tick labels element_text()
axis.title axis titles element_text()
axis.title.x x-axis title element_text()
axis.title.y y-axis title element_text()
axis.ticks axis tick marks element_line()
axis.ticks.length length of tick marks unit()
axis.ticks.margin width of axis tick margin unit()

Let us see an example:

pl + 
  theme(
    axis.line.x = element_line(colour = "green4", size = 1.5),
    axis.line.y = element_line(colour = "green4", linetype = "dashed", size = 1.5),
    axis.text = element_text(color = "springgreen4", size = 15, face = "bold"),
    axis.text.y = element_text(angle = 90, size = rel(0.7), hjust = 0),
    axis.ticks = element_line(colour = "green4", size = 2),
    axis.ticks.x = element_line(size = rel(1.5)),
    axis.title = element_text(size = 20, color = "forestgreen", face = "bold.italic")
)

  • legend theme elements
Theme Element Description Element Function Associated (or Value)
legend.background legend background element_rect()
legend.key background of legend keys element_rect()
legend.key.size legend key size unit()
legend.key.height legend key height unit()
legend.key.width legend key width unit()
legend.margin legend margin unit()
legend.text legend labels element_text()
legend.text.align legend label alignment numeric value
legend.title legend name element_text()
legend.title.align legend name alignment numeric value
legend.position position of legend “left”, “right”, “bottom”, “top”
legend.direction direction of legend keys “horizontal” or “vertical”
legend.justification justification of legend numeric value
legend.box position of multiple legend boxes “horizontal” or “vertical”

Let us see an example:

pl + 
  theme(
    legend.position = "top",
    legend.box = "horizontal",
    legend.background = element_rect(fill = "lemonchiffon", color = "black", size = 1, linetype = "longdash" ),
    legend.key = element_rect(fill = "lemonchiffon", color = "magenta"),
    legend.key.width = unit(0.8, "cm"),
    legend.key.height = unit(0.8, "cm"),
    legend.text = element_text(face = "bold", size = 10),
    legend.title = element_text(face = "bold", size = 12, colour = "magenta")
    )

  • panel theme elements
Theme Element Description Element Function Associated (or Value)
panel.background background of graphics region element_rect()
panel.border border of graphics region element_rect()
panel.grid.major major grid lines element_line()
panel.grid.major.x vertical major grid lines height element_line()
panel.grid.major.y horizontal major grid lines element_line()
panel.grid.minor minor grid lines element_line()
panel.grid.minor.x vertical minor grid lines element_text()
panel.grid.minor.y horizontal minor grid lines element_line()
panel.margin margin between facets numeric value
aspect.ratio plot aspect ratio numeric value

Let us see an example:

pl + 
  theme(
    panel.background = element_rect(fill = "navy", color = "orange", size = 2),
    panel.border = element_rect(fill = NA, colour = "darkorange", size = 2),
    panel.grid.major = element_line(color = "orange", size = 0.3),
    panel.grid.minor = element_blank()
    )

  • facet theme elements
Theme Element Description Element Function Associated
strip.background background of panel strips element_rect()
strip.text strip text element_text()
strip.text.x horizontal strip text element_text()
strip.text.y vertical strip text element_text()

Let us see an example:

ggplot(data = bands, mapping = aes(x= humidity, y = viscosity)) +
  geom_point() + 
  facet_grid(band_type ~ press_type) +
  theme(
    strip.background = element_rect(fill = "#4bb8b6", color = "#265665", size = 2),
    strip.text = element_text(face = "italic", size = 15, colour = "#CC1800"),
    strip.text.y = element_text(face = "bold")
  )

We have already learn about most of these ggplot2 theme elements in the previous chapters, in particular about: axis, legend and facet categories. But what’s about plot and panels theme elements?
With the term “plot” we means what is included outside the plotting area and with “panel” what is included in the plotting area.

In the following paragraphs we will see how to handle with the most common questions about plot and panel customization. We will talk also about the customization of the whole theme function.

Customize the appearance of plotting area

If you want to change the appearance of plotting area you have to set panel_xxx arguments of theme() function.

Change the background of plotting area

panel.background element allows us to modify the background of graphical region and panel.border to modify the border of graphical region. Both panel.background and panel.border are modified by using element_rect() function.

pl + 
  theme(
    panel.background = element_rect(fill="lightblue"),
    panel.border = element_rect(colour="blue", fill=NA, size=2)
)

Pay attention to fill argument for panel.border: you have to specify a blank fill (setting it to NA) for not covering panels.

Customize and remove grid lines

panel.grid.major and panel.grid.minor arguments allows us to customize grid lines by using element_line() function:

pl + 
  theme(
    panel.grid.major = element_line(colour="red"),
    panel.grid.minor = element_line(colour="red", linetype="dashed", size=0.2)
)

If you want to remove grid lines you have to set panel.grid.major and/or panel.grid.minor equal to element_blank():

pl + 
  theme(
    panel.grid.major = element_blank(),
    panel.grid.minor = element_blank()
)

It’s possible to hide just the vertical or horizontal grid lines with panel.grid.major.x, panel.grid.major.y, panel.grid.minor.x and panel.grid.minor.y arguments of theme() function:

pl + 
  theme(
    panel.grid.major.x = element_blank(), # remove horizontal grid major lines 
    panel.grid.minor.y = element_blank()  # remove vertical grid minor lines
)

Customize the plot appearance outside plotting area

If you want to modify plot appearance outside plotting area you have to set plot_xxx arguments of theme() function.

Add the title to a plot and change its appearance

As we saw in Creating a Boxplot chapter, title can be added by using ggtitle() or labs function in this way:

pl + 
  ggtitle("Scatterplot of humidity vs viscosity \n by Pressure type")
pl + 
  labs(title = "Scatterplot of humidity vs viscosity \n by Pressure type")

The previous two command lines produce the same result:

"\n" is used to break the lines.

Title appearance can be changed by setting plot.title argument of theme() function:

pl + 
  ggtitle("Scatterplot of humidity vs viscosity \n by Pressure type") +
  theme(
    plot.title=element_text(size=rel(2), lineheight=0.9, family="Times", face="bold.italic", colour="red")
        )

lineheight arguments refers to interlinear space in plot title.

Change the background outside plotting area

To modify the background set plot.background element of theme() function.

You can change the colour of the background and add a contour line.

pl + 
  theme(
    plot.background = element_rect(fill = "springgreen2",linetype = "solid", colour = "black", size = 2)
)

Change the margins around graphical area

To modify margins around graphical area set plot.margin element of theme() function:

pl + 
  theme(
    plot.margin = unit(x = c(2, 2, 2, 2), units = "cm")
)

unit() is a function that creates a grid unit object of the correct length to use for setting margins. x argument have to be specified as a vector of lenght 4 containing the measure of margins for the four margin of the plotting area, and units argument represents the measurements units. If you want more details about the supported measurements units have a look at the help of unit() function (?unit)

Customize theme function

Change the default theme

If you want to change theme function you have to overwrite the defaut one. Other theme functions are provided by ggplot2 and ggthemes packages.

ggplot2 provides the following theme functions:

  • theme_bw(): a variation on theme_grey() that uses a white background and thin grey grid lines
  • theme_linedraw(): a theme with only black lines of various widths on white backgrounds, reminiscent of a line drawing
  • theme_light(): similar to theme_linedraw() but with ligth grey lines and axes, to direct more attention towards the data
  • theme_dark(): the dark cousin of theme_light(), with similar line sizes but a dark background. Useful to make thin coloured lines pop out
  • theme_minimal(): a minimalistic theme with no background annotations
  • theme_classic(): A classic-looking theme, with x and y axis lines and no gridlines. In ggplot 2.1.0 axes are not visible because of a bug
  • theme_void(): a completely empty theme
pl1 <- pl + theme_bw() + ggtitle("theme_bw()")
pl2 <- pl + theme_linedraw() + ggtitle("theme_linedraw()")
pl3 <- pl + theme_light() + ggtitle("theme_light()")
pl4 <- pl + theme_dark() + ggtitle("theme_dark()")
pl5 <- pl + theme_minimal() + ggtitle("theme_minimal()")
pl6 <- pl + theme_classic() + ggtitle("theme_classic()")
pl7 <- pl + theme_void() + ggtitle("theme_void()")

gridExtra::grid.arrange(pl1, pl2, pl3, pl4, pl5, pl6, pl7, ncol=2)

ggthemes package provides lots of theme functions. Some of them are listed here:

  • theme_tufte(): a minimal ink theme based on Tufte’s The Visual Display of Quantitative Information
  • theme_solarized(): a theme using the solarized color palette
  • theme_excel(): a theme replicating the classic gray charts in Excel
  • theme_few(): theme from Stephen Few’s “Practical Rules for Using Color in Charts”
  • theme_economist(): a theme based on the plots in the The Economist magazine
  • theme_stata(): themes based on Stata graph schemes
  • theme_wsj(): a theme based on the plots in the The Wall Street Journal
pl8 <- pl + theme_tufte() + ggtitle("theme_tufte()") 
pl9 <- pl + theme_solarized() + ggtitle("theme_solarized()") 
pl10 <- pl + theme_excel() + ggtitle("theme_excel()") 
pl11 <- pl + theme_few() + ggtitle("theme_few()") 
pl12 <- pl + theme_economist() + ggtitle("theme_economist()")  
pl13 <- pl + theme_stata() + ggtitle("theme_stata()") 
pl14 <- pl + theme_wsj() + ggtitle("theme_wsj()") 

gridExtra::grid.arrange(pl8, pl9, pl10, pl11, pl12, pl13, pl14, ncol=2)

Chang the default theme for more than one plot

If you want to change the default theme (theme_grey()) for all plots generated in the current R session, you can use theme_set() function. For example, if you want to use white background for all plots run:

theme_set(theme_bw())

Creating your own theme

You can create your own theme by adding elements to an existing theme:

mytheme <- theme_bw() +
theme(text = element_text(colour="slateblue4"),
      axis.title = element_text(size = rel(1.25), face = "bold"),
      legend.title = element_text(size = rel(1.25), face = "bold"),
      plot.background = element_rect(colour ="black")
      )
pl + 
  mytheme